# SRE

Published articles for SRE.

This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles.

## Honoring #IconsOfQuality: Mark Hrynczak

DevFeed: [Honoring #IconsOfQuality: Mark Hrynczak](<https://devfeed.tech/articles/honoring-iconsofquality-mark-hrynczak-27000.md>)

Original publisher: [Read original article](<https://www.browserstack.com/blog/honoring-icons-of-quality-mark-hrynczak/>)

Author: Rajrupa Roychowdhury

Published: 2026-09-16T08:20:52Z

Content type: opinion

Language: en

Sources: [BrowserStack Blog](<https://devfeed.tech/sources/browserstack-blog.md>)

Topics: [Testing](<https://devfeed.tech/topics/testing.md>), [Loop Engineering](<https://devfeed.tech/topics/loop-engineering.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [site-reliability-engineering](<https://devfeed.tech/topics/site-reliability-engineering.md>), [Amazon Web Services](<https://devfeed.tech/topics/aws.md>), [atlassian](<https://devfeed.tech/topics/atlassian.md>)

Tags: [agentic](<https://devfeed.tech/tags/agentic.md>), [ai](<https://devfeed.tech/tags/ai.md>), [atlassian](<https://devfeed.tech/tags/atlassian.md>), [aws](<https://devfeed.tech/tags/aws.md>), [icons-of-quality](<https://devfeed.tech/tags/icons-of-quality.md>), [quality](<https://devfeed.tech/tags/quality.md>), [sre](<https://devfeed.tech/tags/sre.md>), [testing](<https://devfeed.tech/tags/testing.md>), [tooling](<https://devfeed.tech/tags/tooling.md>)

### AI overview

BrowserStack profiles Mark Hrynczak, Canva's Head of Quality and QA Director, discussing how distributed quality ownership, agentic testing, and AI-driven decision support can help engineering teams move faster while maintaining reliability.

### Source excerpt

To celebrate the relentless passion and invaluable contributions of leaders in software quality, BrowserStack is proud to honour Icons of Quality.

## Agents operate, humans govern: Scale your operations and reduce toil with Azure SRE Agent

DevFeed: [Agents operate, humans govern: Scale your operations and reduce toil with Azure SRE Agent](<https://devfeed.tech/articles/agents-operate-humans-govern-scale-your-operations-and-reduce-toil-with-azure-sre-agent-26948.md>)

Original publisher: [Read original article](<https://thenewstack.io/azure-sre-agent-operations/>)

Author: TNS Staff

Published: 2026-09-15T16:21:45Z

Content type: article

Language: en

Sources: [The New Stack](<https://devfeed.tech/sources/the-new-stack.md>)

Topics: [SRE](<https://devfeed.tech/topics/sre.md>), [incident](<https://devfeed.tech/topics/incident.md>), [Azure](<https://devfeed.tech/topics/azure.md>), [observability](<https://devfeed.tech/topics/observability.md>), [DevOps](<https://devfeed.tech/topics/devops.md>), [Redis](<https://devfeed.tech/topics/redis.md>)

Tags: [agent](<https://devfeed.tech/tags/agent.md>), [ai-agents](<https://devfeed.tech/tags/ai-agents.md>), [ai-operations](<https://devfeed.tech/tags/ai-operations.md>), [azure](<https://devfeed.tech/tags/azure.md>), [code-review](<https://devfeed.tech/tags/code-review.md>), [deployment](<https://devfeed.tech/tags/deployment.md>), [devops](<https://devfeed.tech/tags/devops.md>), [incident](<https://devfeed.tech/tags/incident.md>), [microsoft-azure](<https://devfeed.tech/tags/microsoft-azure.md>), [monitoring](<https://devfeed.tech/tags/monitoring.md>), [observability](<https://devfeed.tech/tags/observability.md>), [post](<https://devfeed.tech/tags/post.md>), [redis](<https://devfeed.tech/tags/redis.md>), [sponsor-microsoft-azure](<https://devfeed.tech/tags/sponsor-microsoft-azure.md>), [sponsored](<https://devfeed.tech/tags/sponsored.md>), [sponsored-post](<https://devfeed.tech/tags/sponsored-post.md>), [sre](<https://devfeed.tech/tags/sre.md>), [telemetry](<https://devfeed.tech/tags/telemetry.md>)

### AI overview

The article describes Azure SRE Agent as a system that analyzes telemetry, correlates deployment and monitoring data, investigates incidents, identifies root causes, recommends or prepares fixes, and supports mitigation and other operational tasks under human approval. It cites examples involving Microsoft service teams and InEight, including a recommendation to scale Redis.

### Source excerpt

What if engineers could spend their time building and optimizing systems rather than maintaining them? It's 3 a.m., and the The post Agents operate, humans govern: Scale your operations and reduce toil with Azure SRE Agent appeared first on The New Stack.

## How We Built Automated Capacity Testing for Kafka Consumers

DevFeed: [How We Built Automated Capacity Testing for Kafka Consumers](<https://devfeed.tech/articles/how-we-built-automated-capacity-testing-for-kafka-consumers-23723.md>)

Original publisher: [Read original article](<https://medium.com/booking-com-development/how-we-built-automated-capacity-testing-for-kafka-consumers-1853623bce78?source=rss----1c36c35f9c76---4>)

Author: Kaan Karakaya

Published: 2026-09-14T09:46:34Z

Content type: tutorial

Language: en

Sources: [Booking.com Development - Medium](<https://devfeed.tech/sources/booking-com-development-medium.md>)

Topics: [Kafka](<https://devfeed.tech/topics/kafka.md>), [Testing](<https://devfeed.tech/topics/testing.md>), [HTTP](<https://devfeed.tech/topics/http.md>)

Tags: [automated](<https://devfeed.tech/tags/automated.md>), [capacity](<https://devfeed.tech/tags/capacity.md>), [health-checks](<https://devfeed.tech/tags/health-checks.md>), [kafka](<https://devfeed.tech/tags/kafka.md>), [load](<https://devfeed.tech/tags/load.md>), [load-balancer](<https://devfeed.tech/tags/load-balancer.md>), [parallelism](<https://devfeed.tech/tags/parallelism.md>), [partition](<https://devfeed.tech/tags/partition.md>), [recovery](<https://devfeed.tech/tags/recovery.md>), [scale](<https://devfeed.tech/tags/scale.md>), [site-reliability-engineer](<https://devfeed.tech/tags/site-reliability-engineer.md>), [sre](<https://devfeed.tech/tags/sre.md>), [testing](<https://devfeed.tech/tags/testing.md>)

### AI overview

This article describes Booking.com's extension of an existing capacity-testing platform for Kafka consumers. It explains how changing partition assignment can provide a controlled, measurable way to test consumer throughput and whether remaining consumers can absorb reassigned work after an instance or failure domain disappears.

### Source excerpt

Photo by GuerrillaBuzz on Unsplash Kafka makes it easy to distribute work across consumer instances. It is much harder to prove, safely and repeatedly, how those instances behave when the distribution changes and one of them has to carry more than its usual share. For teams that run Kafka at scale, this is a practical reliability question: how much load can a consumer instance actually handle? We had automated capacity testing for HTTP services, but Kafka consumers were still tested with manual drills. Those drills could tell us something, but they were disruptive, difficult to reproduce, and risky precisely when the system was close to its limit. We wanted a controlled way to answer three questions: What is the maximum sustainable throughput of a consumer instance? If an instance or failure domain disappears, can the remaining consumers absorb the reassigned work? Are we overprovisioning resources because we do not know the real limit? The result was an extension to our capacity-testing platform that turns Kafka partition assignment into a safe, measurable load-control mechanism. Why HTTP capacity testing did not translate Our existing platform was designed for request-response services behind a load balancer. A scheduled test selects one instance, routes an increasing share of traffic to it, runs health checks after each step, and records the highest ratio the instance can sustain. After the test, traffic returns to its normal distribution and the result is reported to the service owner. Kafka has no equivalent traffic knob. Consumers pull records, and the unit of parallelism is the partition. Within a consumer group, each partition is owned by one consumer at a time. If a topic has 12 partitions and four equally loaded instances, each instance owns about three. When one instance disappears, a rebalance gives the survivors more partitions -- and the extra work arrives as a step change, not as a smooth increase from a load balancer. The key translation: for an HTTP

## A working incident response model for GPU clouds

DevFeed: [A working incident response model for GPU clouds](<https://devfeed.tech/articles/a-working-incident-response-model-for-gpu-clouds-34012.md>)

Original publisher: [Read original article](<https://sridharrajarao.com/blog/gpu-cloud-incident-response-model/>)

Author: Sridhar Rajarao

Published: 2026-09-12T00:00:00Z

Content type: article

Language: en

Sources: [Sridhar Rajarao](<https://devfeed.tech/sources/sridhar-rajarao.md>)

Topics: [incident](<https://devfeed.tech/topics/incident.md>), [Incident response](<https://devfeed.tech/topics/incident-response.md>), [GPU](<https://devfeed.tech/topics/gpu.md>), [Monitoring](<https://devfeed.tech/topics/monitoring.md>), [Tooling](<https://devfeed.tech/topics/tooling.md>)

Tags: [communication](<https://devfeed.tech/tags/communication.md>), [debugging](<https://devfeed.tech/tags/debugging.md>), [gpu](<https://devfeed.tech/tags/gpu.md>), [gpu-cloud](<https://devfeed.tech/tags/gpu-cloud.md>), [grafana](<https://devfeed.tech/tags/grafana.md>), [incident](<https://devfeed.tech/tags/incident.md>), [incident-management](<https://devfeed.tech/tags/incident-management.md>), [incident-response](<https://devfeed.tech/tags/incident-response.md>), [jira](<https://devfeed.tech/tags/jira.md>), [management](<https://devfeed.tech/tags/management.md>), [on-call](<https://devfeed.tech/tags/on-call.md>), [operations](<https://devfeed.tech/tags/operations.md>), [ownership](<https://devfeed.tech/tags/ownership.md>), [pagerduty](<https://devfeed.tech/tags/pagerduty.md>), [review](<https://devfeed.tech/tags/review.md>), [slack](<https://devfeed.tech/tags/slack.md>), [sre](<https://devfeed.tech/tags/sre.md>)

### AI overview

This article presents an incident response model for GPU clouds and other customer-facing infrastructure businesses. It emphasizes preparation, named ownership, meaningful alert paths, incident command, separation of technical work from customer communication, and post-incident learning. It argues that tools such as PagerDuty, Jira, Grafana, and Slack are useful only within a clear operating model.

### Source excerpt

The tools matter, but they only work when they sit inside a clear operating model: ownership, signal, command, communication, and learning.

## Every service needs an owner

DevFeed: [Every service needs an owner](<https://devfeed.tech/articles/every-service-needs-an-owner-34011.md>)

Original publisher: [Read original article](<https://sridharrajarao.com/blog/every-service-needs-an-owner/>)

Author: Sridhar Rajarao

Published: 2026-09-12T00:00:00Z

Content type: article

Language: en

Sources: [Sridhar Rajarao](<https://devfeed.tech/sources/sridhar-rajarao.md>)

Topics: [systems](<https://devfeed.tech/topics/systems.md>), [incident](<https://devfeed.tech/topics/incident.md>)

Tags: [catalog](<https://devfeed.tech/tags/catalog.md>), [customer](<https://devfeed.tech/tags/customer.md>), [incident](<https://devfeed.tech/tags/incident.md>), [on-call](<https://devfeed.tech/tags/on-call.md>), [ownership](<https://devfeed.tech/tags/ownership.md>), [platform-engineering](<https://devfeed.tech/tags/platform-engineering.md>), [production](<https://devfeed.tech/tags/production.md>), [reliability](<https://devfeed.tech/tags/reliability.md>), [service](<https://devfeed.tech/tags/service.md>), [service-catalog](<https://devfeed.tech/tags/service-catalog.md>), [sre](<https://devfeed.tech/tags/sre.md>), [startups](<https://devfeed.tech/tags/startups.md>), [team](<https://devfeed.tech/tags/team.md>)

### AI overview

The article argues that growing organizations need a focused service catalog to make production ownership visible. It recommends recording each service's customer outcome, owning team, current on-call contact, deployment path, health dashboard, runbook, and dependencies, and maintaining those records as part of engineering work.

### Source excerpt

A useful service catalog is not an inventory project. It is a public record of who owns a customer outcome when the system is healthy and when it fails.

## How we shipped 15 Tbps for OpenAI in 90 days (Session 2 of 3)

DevFeed: [How we shipped 15 Tbps for OpenAI in 90 days (Session 2 of 3)](<https://devfeed.tech/articles/how-we-shipped-15-tbps-for-openai-in-90-days-session-2-of-3-34018.md>)

Original publisher: [Read original article](<https://sridharrajarao.com/blog/openai-15-tbps-session-2/>)

Author: Sridhar Rajarao

Published: 2026-09-12T00:00:00Z

Content type: article

Language: en

Sources: [Sridhar Rajarao](<https://devfeed.tech/sources/sridhar-rajarao.md>)

Topics: [OpenAI](<https://devfeed.tech/topics/openai.md>), [Network](<https://devfeed.tech/topics/network.md>), [GPU](<https://devfeed.tech/topics/gpu.md>), [Server](<https://devfeed.tech/topics/server.md>), [Cache](<https://devfeed.tech/topics/cache.md>), [API](<https://devfeed.tech/topics/api.md>), [Oracle Database](<https://devfeed.tech/topics/oracle-database.md>)

Tags: [api](<https://devfeed.tech/tags/api.md>), [architecture](<https://devfeed.tech/tags/architecture.md>), [build](<https://devfeed.tech/tags/build.md>), [cache](<https://devfeed.tech/tags/cache.md>), [capacity](<https://devfeed.tech/tags/capacity.md>), [database](<https://devfeed.tech/tags/database.md>), [debugging](<https://devfeed.tech/tags/debugging.md>), [execution](<https://devfeed.tech/tags/execution.md>), [gateway](<https://devfeed.tech/tags/gateway.md>), [gpu](<https://devfeed.tech/tags/gpu.md>), [network](<https://devfeed.tech/tags/network.md>), [object](<https://devfeed.tech/tags/object.md>), [openai](<https://devfeed.tech/tags/openai.md>), [performance](<https://devfeed.tech/tags/performance.md>), [platform-engineering](<https://devfeed.tech/tags/platform-engineering.md>), [server](<https://devfeed.tech/tags/server.md>), [servers](<https://devfeed.tech/tags/servers.md>), [sre](<https://devfeed.tech/tags/sre.md>), [storage](<https://devfeed.tech/tags/storage.md>), [testing](<https://devfeed.tech/tags/testing.md>), [warp](<https://devfeed.tech/tags/warp.md>)

### AI overview

The second session describes turning an architecture for OpenAI's 15 Tbps system into a delivery plan. It covers coordinated capacity planning across network, gateway, server, storage, and database teams; caching object names through the Inventory API; delivery tracking; and performance validation. Early WARP testing found packet drops caused by an unsuitable MTU of 1500, which was changed to 9100.

### Source excerpt

Architecture was only the first week. Session 2 is about the build: capacity, execution discipline, and the first signs that performance would be the real test.

## Why a DevOps Portal Cannot Replace an Operating Model

DevFeed: [Why a DevOps Portal Cannot Replace an Operating Model](<https://devfeed.tech/articles/build-the-platform-not-the-portal-34009.md>)

Original publisher: [Read original article](<https://sridharrajarao.com/blog/devops-portal-wont-fix-operations/>)

Author: Sridhar Rajarao

Published: 2026-09-11T00:00:00Z

Content type: opinion

Language: en

Sources: [Sridhar Rajarao](<https://devfeed.tech/sources/sridhar-rajarao.md>)

Topics: [DevOps](<https://devfeed.tech/topics/devops.md>), [incident](<https://devfeed.tech/topics/incident.md>), [Deployment](<https://devfeed.tech/topics/deployment.md>)

Tags: [deploy](<https://devfeed.tech/tags/deploy.md>), [deployment](<https://devfeed.tech/tags/deployment.md>), [devops](<https://devfeed.tech/tags/devops.md>), [incident](<https://devfeed.tech/tags/incident.md>), [operations](<https://devfeed.tech/tags/operations.md>), [platform-engineering](<https://devfeed.tech/tags/platform-engineering.md>), [production](<https://devfeed.tech/tags/production.md>), [sre](<https://devfeed.tech/tags/sre.md>), [startups](<https://devfeed.tech/tags/startups.md>)

### AI overview

A DevOps portal can reduce operational friction, but it cannot create service ownership, incident discipline, or an operating model. The article recommends defining ownership, health signals, runbooks, escalation paths, and rollback practices before building a small, practical portal.

### Source excerpt

A portal can remove friction. It cannot create service ownership, incident discipline, or a working operating model that does not yet exist.

## Contributing to OpenSRE and Integrating It with Yandex Cloud

DevFeed: [Contributing to OpenSRE and Integrating It with Yandex Cloud](<https://devfeed.tech/articles/350-24896.md>)

Original publisher: [Read original article](<https://habr.com/ru/companies/yandex/articles/1080524/>)

Author: nowhere\_in\_space (Яндекс, Yandex Cloud & Yandex Infrastructure)

Published: 2026-09-10T07:00:10Z

Content type: article

Language: ru

Sources: [Яндекс - Как мы делаем Яндекс / Статьи](<https://devfeed.tech/sources/source.md>)

Topics: [SRE](<https://devfeed.tech/topics/sre.md>), [Cloud](<https://devfeed.tech/topics/cloud.md>), [GitHub](<https://devfeed.tech/topics/github.md>)

Tags: [ai-e2239b5ae8fa](<https://devfeed.tech/tags/ai-e2239b5ae8fa.md>), [cloud](<https://devfeed.tech/tags/cloud.md>), [kubernetes](<https://devfeed.tech/tags/kubernetes.md>), [llm](<https://devfeed.tech/tags/llm.md>), [opensre](<https://devfeed.tech/tags/opensre.md>), [postgresql](<https://devfeed.tech/tags/postgresql.md>), [sre](<https://devfeed.tech/tags/sre.md>), [tag-831b63de9433](<https://devfeed.tech/tags/tag-831b63de9433.md>), [tag-e1321f9c36de](<https://devfeed.tech/tags/tag-e1321f9c36de.md>)

### AI overview

The author describes contributing to OpenSRE, an early public-alpha tool for AI SRE agents that investigate and resolve production incidents, and pursuing an integration with Yandex Cloud. The article cautions that OpenSRE's safety is not guaranteed and recommends running it without modifying permissions.

### Source excerpt

Представьте: ночной алерт, приложение отдаёт пятисотки, но само оно живо. Понятно, что дальше начнётся знакомое -- вкладки с графиками, поиски в логах и попытки понять, кто и что изменил. Сколько на это обычно уходит времени? А что, если вместе с вами в инциденте будет разбираться ИИ-агент? Привет! Я Антон Воронцов, CRE в Yandex Cloud. В конце июля я в очередной раз листал свежие репозитории на GitHub, чтобы посмотреть, что происходит в моих смежных дисциплинах: SRE, автоматизациях и, понятное дело, ИИ. Вдруг я наткнулся на один интересный репозиторий, который активно рос: количество звёзд, коммиты и заинтересованные люди из разных стран -- всё это про OpenSRE. Эта статья о том, как я впервые контрибьютил во внешний проект, что стало самым сложным и как вообще работает этот инструмент. Читать далее

## How cloud native goes AI native

DevFeed: [How cloud native goes AI native](<https://devfeed.tech/articles/how-cloud-native-goes-ai-native-4600.md>)

Original publisher: [Read original article](<https://www.cncf.io/blog/2026/09/09/how-cloud-native-goes-ai-native/>)

Author: Doron Grinstein, CEO of Control Plane

Published: 2026-09-09T08:13:23Z

Content type: opinion

Language: en

Sources: [Cloud Native Computing Foundation](<https://devfeed.tech/sources/cloud-native-computing-foundation.md>)

Topics: [cloud-infrastructure](<https://devfeed.tech/topics/cloud-infrastructure.md>), [App](<https://devfeed.tech/topics/app.md>), [coding](<https://devfeed.tech/topics/coding.md>), [site-reliability-engineering](<https://devfeed.tech/topics/site-reliability-engineering.md>), [Database](<https://devfeed.tech/topics/database.md>), [Claude](<https://devfeed.tech/topics/claude.md>), [cursor](<https://devfeed.tech/topics/cursor.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [apps](<https://devfeed.tech/tags/apps.md>), [blog](<https://devfeed.tech/tags/blog.md>), [claude](<https://devfeed.tech/tags/claude.md>), [cloud](<https://devfeed.tech/tags/cloud.md>), [cursor](<https://devfeed.tech/tags/cursor.md>), [infrastructure](<https://devfeed.tech/tags/infrastructure.md>), [production](<https://devfeed.tech/tags/production.md>), [sre](<https://devfeed.tech/tags/sre.md>)

### AI overview

The article argues that AI-assisted, "vibe-coded" applications are increasingly easy to start but often fail to reach production because they bypass cloud-native operational practices. It frames closing that production-readiness gap as a key infrastructure challenge.

### Source excerpt

"A sales guy writing code" used to be the lead-up to a joke. But now no one's laughing. Designers used to sit meekly waiting for the high priests of code to make their designs real. Now...

## See you at Elastic{ON} 2026

DevFeed: [See you at Elastic{ON} 2026](<https://devfeed.tech/articles/see-you-at-elastic-on-2026-4818.md>)

Original publisher: [Read original article](<https://www.elastic.co/blog/elasticon-2026>)

Author: Dan Courcy

Published: 2026-09-08T00:00:00Z

Content type: news

Language: en

Sources: [Elastic Blog - Elasticsearch, Kibana, and ELK Stack](<https://devfeed.tech/sources/elastic-blog-elasticsearch-kibana-and-elk-stack.md>)

Topics: [AI search](<https://devfeed.tech/topics/ai-search.md>), [telemetry](<https://devfeed.tech/topics/telemetry.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [ai-agent](<https://devfeed.tech/tags/ai-agent.md>), [developer](<https://devfeed.tech/tags/developer.md>), [elasticsearch](<https://devfeed.tech/tags/elasticsearch.md>), [event](<https://devfeed.tech/tags/event.md>), [logging](<https://devfeed.tech/tags/logging.md>), [metrics](<https://devfeed.tech/tags/metrics.md>), [observability](<https://devfeed.tech/tags/observability.md>), [platform-observability-search-security](<https://devfeed.tech/tags/platform-observability-search-security.md>), [production](<https://devfeed.tech/tags/production.md>), [search](<https://devfeed.tech/tags/search.md>), [sre](<https://devfeed.tech/tags/sre.md>)

### AI overview

Elastic announces its Elastic{ON} 2026 global event tour, with sessions for developers on scaling AI agents with Elasticsearch and for SREs on observability, logging, metrics, and AI-assisted incident response.

### Source excerpt

Elastic{ON} kicks off this September with seven stops in cities around the world. Elastic's CEO Ash Kulkarni will be appearing at stops across the tour, opening keynotes with a candid conversation about why your data has never been more valuable.

## Focus and followthrough are the moat

DevFeed: [Focus and followthrough are the moat](<https://devfeed.tech/articles/focus-and-followthrough-are-the-moat-37621.md>)

Original publisher: [Read original article](<https://swizec.com/blog/focus-and-followthrough-are-the-moat>)

Author: hi@swizec.com (Swizec Teller)

Published: 2026-08-27T00:00:00Z

Content type: opinion

Language: en

Sources: [Swizec Teller](<https://devfeed.tech/sources/swizec-teller.md>)

Topics: [Development](<https://devfeed.tech/topics/development.md>), [SRE](<https://devfeed.tech/topics/sre.md>)

Tags: [development](<https://devfeed.tech/tags/development.md>), [focus](<https://devfeed.tech/tags/focus.md>), [production](<https://devfeed.tech/tags/production.md>), [projects](<https://devfeed.tech/tags/projects.md>), [sre](<https://devfeed.tech/tags/sre.md>), [team](<https://devfeed.tech/tags/team.md>)

### AI overview

An opinion piece about how a small startup team uses focus, sprint planning, prioritization, and regular stakeholder communication to finish work despite having more requests than capacity.

### Source excerpt

Because starting is easy and finishing is hard.

## Investigating Redis Client Failures After a Node Loss at hh.ru

DevFeed: [Investigating Redis Client Failures After a Node Loss at hh.ru](<https://devfeed.tech/articles/redis-30674.md>)

Original publisher: [Read original article](<https://habr.com/ru/companies/hh/articles/1074194/>)

Author: nicholasgribanov (hh.ru)

Published: 2026-08-26T05:30:49Z

Content type: article

Language: ru

Sources: [HeadHunter RU](<https://devfeed.tech/sources/headhunter-ru.md>)

Topics: [Redis](<https://devfeed.tech/topics/redis.md>)

Tags: [consul](<https://devfeed.tech/tags/consul.md>), [downtime](<https://devfeed.tech/tags/downtime.md>), [java](<https://devfeed.tech/tags/java.md>), [jedis](<https://devfeed.tech/tags/jedis.md>), [redis](<https://devfeed.tech/tags/redis.md>), [sre](<https://devfeed.tech/tags/sre.md>), [tag-1d4e49052118](<https://devfeed.tech/tags/tag-1d4e49052118.md>), [tag-68e701e78517](<https://devfeed.tech/tags/tag-68e701e78517.md>), [tag-b0a411324cb6](<https://devfeed.tech/tags/tag-b0a411324cb6.md>), [tag-b92bf5906bbd](<https://devfeed.tech/tags/tag-b92bf5906bbd.md>), [tag-dfac9042ce7b](<https://devfeed.tech/tags/tag-dfac9042ce7b.md>), [timeout](<https://devfeed.tech/tags/timeout.md>)

### AI overview

A Platform team at hh.ru investigates incidents in its internal Redis client, including a 57-minute outage after a Redis node was lost. The team used controlled-load testing, Jedis updates, timeout and pool experiments, new metrics, and logs to trace the failures to a code issue and improve client stability.

### Source excerpt

Пару лет назад мы устроили настоящее расследование серии инцидентов в поисках скрытого дефекта нашего Redis-клиента. Команда воспроизводила сбои под контролируемой нагрузкой, проверяла одну гипотезу за другой, обновляла Jedis, экспериментировала с таймаутами и размерами пулов -- но ничего не помогало. А помогли новые метрики и логи, настойчивость команды, ночные эксперименты и готовность разбирать поведение системы до последнего соединения. Получилась история с неожиданными поворотами, ложными следами и одной лишней строчкой кода в роли главного подозреваемого -- а её итогом стал Redis-клиент, который оказался устойчивее, чем был до начала расследования. Меня зовут Коля Грибанов, я тимлид команды "Платформа" в hh.ru. В статье расскажу, почему потеря одной ноды Redis вызывала шторм из десятков тысяч соединений, и как мы шаг за шагом искали причину инцидентов. Читать далее

## Try Azure SRE Agent with no always-on charges

DevFeed: [Try Azure SRE Agent with no always-on charges](<https://devfeed.tech/articles/try-azure-sre-agent-with-no-always-on-charges-23836.md>)

Original publisher: [Read original article](<https://devblogs.microsoft.com/blog/try-azure-sre-agent-with-no-always-on-charges/>)

Author: Nir Mashkowski

Published: 2026-08-25T15:00:00Z

Content type: release

Language: en

Sources: [Developer Blogs](<https://devfeed.tech/sources/developer-blogs.md>)

Topics: [Azure](<https://devfeed.tech/topics/azure.md>), [site-reliability-engineering](<https://devfeed.tech/topics/site-reliability-engineering.md>), [telemetry](<https://devfeed.tech/topics/telemetry.md>), [incident management](<https://devfeed.tech/topics/incident-management.md>), [Cloud](<https://devfeed.tech/topics/cloud.md>)

Tags: [announcement](<https://devfeed.tech/tags/announcement.md>), [azure](<https://devfeed.tech/tags/azure.md>), [cloud](<https://devfeed.tech/tags/cloud.md>), [incident-management](<https://devfeed.tech/tags/incident-management.md>), [microsoft](<https://devfeed.tech/tags/microsoft.md>), [microsoft-for-developers](<https://devfeed.tech/tags/microsoft-for-developers.md>), [sre](<https://devfeed.tech/tags/sre.md>), [telemetry](<https://devfeed.tech/tags/telemetry.md>)

### AI overview

Microsoft announces a 30-day trial for Azure SRE Agent with no charges for setup time or keeping agents ready. The announcement also covers general availability of VNet integration and public preview of Live Reports. Active Azure Agent Unit charges apply when agents perform work.

### Source excerpt

We are happy to announce a 30-day trial experience for Azure SRE Agent. New customers can create and configure the SRE Agent at their own pace, with no charges for setup time or keeping agents ready. During the trial, you can connect your agents to telemetry, source code, incident management platforms, and other operational tools, [...] The post Try Azure SRE Agent with no always-on charges appeared first on Microsoft for Developers.

## Why GitHub feels less reliable lately

DevFeed: [Why GitHub feels less reliable lately](<https://devfeed.tech/articles/why-github-feels-less-reliable-lately-34026.md>)

Original publisher: [Read original article](<https://sridharrajarao.com/blog/why-github-feels-less-reliable/>)

Author: Sridhar Rajarao

Published: 2026-08-23T00:00:00Z

Content type: opinion

Language: en

Sources: [Sridhar Rajarao](<https://devfeed.tech/sources/sridhar-rajarao.md>)

Topics: [GitHub](<https://devfeed.tech/topics/github.md>), [incident](<https://devfeed.tech/topics/incident.md>), [migration](<https://devfeed.tech/topics/migration.md>), [systems](<https://devfeed.tech/topics/systems.md>), [Azure](<https://devfeed.tech/topics/azure.md>), [GitHub Actions](<https://devfeed.tech/topics/github-actions.md>), [pull-requests](<https://devfeed.tech/topics/pull-requests.md>)

Tags: [autoscaling](<https://devfeed.tech/tags/autoscaling.md>), [capacity](<https://devfeed.tech/tags/capacity.md>), [concurrency](<https://devfeed.tech/tags/concurrency.md>), [data-centers](<https://devfeed.tech/tags/data-centers.md>), [deployment](<https://devfeed.tech/tags/deployment.md>), [github](<https://devfeed.tech/tags/github.md>), [incident](<https://devfeed.tech/tags/incident.md>), [incident-management](<https://devfeed.tech/tags/incident-management.md>), [istio](<https://devfeed.tech/tags/istio.md>), [reliability](<https://devfeed.tech/tags/reliability.md>), [request](<https://devfeed.tech/tags/request.md>), [resilience](<https://devfeed.tech/tags/resilience.md>), [sre](<https://devfeed.tech/tags/sre.md>), [transformation](<https://devfeed.tech/tags/transformation.md>)

### AI overview

The article argues that GitHub's recent reliability problems reflect the difficult middle of a major infrastructure transformation. It connects incidents to migration complexity, unsafe automation, configuration mistakes, capacity and concurrency weaknesses, database migration errors, and autoscaling problems.

### Source excerpt

GitHub is not having one outage problem. Its recent incident reports show the difficult middle of a platform transformation.

## Centralize human and agentic work with Datadog Work Management

DevFeed: [Centralize human and agentic work with Datadog Work Management](<https://devfeed.tech/articles/centralize-human-and-agentic-work-with-datadog-work-management-2319.md>)

Original publisher: [Read original article](<https://www.datadoghq.com/blog/work-management/>)

Author: Roxanne Moslehi

Published: 2026-08-18T00:00:00Z

Content type: article

Language: en

Sources: [Datadog | The Monitor blog](<https://devfeed.tech/sources/datadog-the-monitor-blog.md>)

Topics: [AI Agent](<https://devfeed.tech/topics/ai-agent.md>), [incident](<https://devfeed.tech/topics/incident.md>), [site-reliability-engineering](<https://devfeed.tech/topics/site-reliability-engineering.md>), [Slack](<https://devfeed.tech/topics/slack.md>), [SRE](<https://devfeed.tech/topics/sre.md>), [SIEM, Security](<https://devfeed.tech/topics/siem-security.md>), [GitHub](<https://devfeed.tech/topics/github.md>), [error tracking](<https://devfeed.tech/topics/error-tracking.md>), [dashboards](<https://devfeed.tech/topics/dashboards.md>), [Traces](<https://devfeed.tech/topics/traces.md>)

Tags: [agentic](<https://devfeed.tech/tags/agentic.md>), [ai](<https://devfeed.tech/tags/ai.md>), [ai-agent](<https://devfeed.tech/tags/ai-agent.md>), [cloud-siem](<https://devfeed.tech/tags/cloud-siem.md>), [dashboards](<https://devfeed.tech/tags/dashboards.md>), [devops](<https://devfeed.tech/tags/devops.md>), [devsecops](<https://devfeed.tech/tags/devsecops.md>), [error-tracking](<https://devfeed.tech/tags/error-tracking.md>), [github](<https://devfeed.tech/tags/github.md>), [incident](<https://devfeed.tech/tags/incident.md>), [management](<https://devfeed.tech/tags/management.md>), [slack](<https://devfeed.tech/tags/slack.md>), [sre](<https://devfeed.tech/tags/sre.md>), [traces](<https://devfeed.tech/tags/traces.md>), [work-management](<https://devfeed.tech/tags/work-management.md>), [workflow-automation](<https://devfeed.tech/tags/workflow-automation.md>)

### AI overview

Datadog Work Management centralizes work created by people, automations, and Datadog AI agents. It preserves context from logs, traces, monitors, alerts, ownership, assignments, approvals, artifacts, and activity while integrating with Datadog and external collaboration systems.

### Source excerpt

Learn how Datadog Work Management helps you coordinate human and AI agent-driven work while preserving context, ownership, and activity across tools.

## Understanding Load Balancing for Beginners

DevFeed: [Understanding Load Balancing for Beginners](<https://devfeed.tech/articles/understanding-load-balancing-for-beginners-17489.md>)

Original publisher: [Read original article](<https://kodekloud.com/blog/understanding-load-balancing-for-beginners/>)

Author: Pramodh Kumar M

Published: 2026-08-17T17:00:34Z

Content type: tutorial

Language: en

Sources: [Kubernetes - KodeKloud Blog | DevOps, Cloud, Kubernetes, AI Tutorials & More](<https://devfeed.tech/sources/kubernetes-kodekloud-blog-devops-cloud-kubernetes-ai-tutorials-more.md>)

Topics: [backends](<https://devfeed.tech/topics/backends.md>), [networking](<https://devfeed.tech/topics/networking.md>), [Algorithms](<https://devfeed.tech/topics/algorithms.md>)

Tags: [backend](<https://devfeed.tech/tags/backend.md>), [beginners](<https://devfeed.tech/tags/beginners.md>), [cloud](<https://devfeed.tech/tags/cloud.md>), [connection-draining](<https://devfeed.tech/tags/connection-draining.md>), [devops](<https://devfeed.tech/tags/devops.md>), [failover](<https://devfeed.tech/tags/failover.md>), [health-checks](<https://devfeed.tech/tags/health-checks.md>), [high-availability](<https://devfeed.tech/tags/high-availability.md>), [kubernetes](<https://devfeed.tech/tags/kubernetes.md>), [layer-4-vs-layer-7](<https://devfeed.tech/tags/layer-4-vs-layer-7.md>), [least-connections](<https://devfeed.tech/tags/least-connections.md>), [load-balancer](<https://devfeed.tech/tags/load-balancer.md>), [load-balancer-for-beginners](<https://devfeed.tech/tags/load-balancer-for-beginners.md>), [load-balancing](<https://devfeed.tech/tags/load-balancing.md>), [load-balancing-algorithms](<https://devfeed.tech/tags/load-balancing-algorithms.md>), [networking](<https://devfeed.tech/tags/networking.md>), [nginx](<https://devfeed.tech/tags/nginx.md>), [round-robin](<https://devfeed.tech/tags/round-robin.md>), [session-affinity](<https://devfeed.tech/tags/session-affinity.md>), [sre](<https://devfeed.tech/tags/sre.md>), [sticky-sessions](<https://devfeed.tech/tags/sticky-sessions.md>), [thundering-herd](<https://devfeed.tech/tags/thundering-herd.md>), [traffic-management](<https://devfeed.tech/tags/traffic-management.md>)

### AI overview

This beginner-oriented article explains load balancing as both traffic distribution and backend failure detection. It compares round robin and least-connections algorithms, distinguishes Layer 4 from Layer 7 routing, and discusses health checks, failover, draining, sticky sessions, and the risks of overly aggressive checks.

### Source excerpt

Spreading traffic is the easy half of load balancing. The half that decides whether an outage lasts ten seconds or ten minutes is noticing that a backend has stopped working, and most health checks cannot.

## Using observability to verify TLS certificate rotation in production

DevFeed: [Using observability to verify TLS certificate rotation in production](<https://devfeed.tech/articles/your-tls-rotation-is-not-reliable-until-production-proves-it-34025.md>)

Original publisher: [Read original article](<https://sridharrajarao.com/blog/tls-rotation-observability/>)

Author: Sridhar Rajarao

Published: 2026-08-13T00:00:00Z

Content type: article

Language: en

Sources: [Sridhar Rajarao](<https://devfeed.tech/sources/sridhar-rajarao.md>)

Topics: [TLS (Transport Layer Security)](<https://devfeed.tech/topics/tls.md>), [observability](<https://devfeed.tech/topics/observability.md>), [TLS handshake](<https://devfeed.tech/topics/tls-handshake.md>), [Automation](<https://devfeed.tech/topics/automation.md>), [nginx](<https://devfeed.tech/topics/nginx.md>), [Kubernetes](<https://devfeed.tech/topics/kubernetes.md>)

Tags: [automation](<https://devfeed.tech/tags/automation.md>), [nginx](<https://devfeed.tech/tags/nginx.md>), [observability](<https://devfeed.tech/tags/observability.md>), [reliability](<https://devfeed.tech/tags/reliability.md>), [sre](<https://devfeed.tech/tags/sre.md>), [tls](<https://devfeed.tech/tags/tls.md>), [tls-handshake](<https://devfeed.tech/tags/tls-handshake.md>)

### AI overview

The article explains that automating certificate renewal does not prove that production endpoints serve the new certificate. It recommends externally probing customer-facing endpoints and measuring certificate details and real TLS handshakes across proxies, regions, ingress controllers, CDNs, gateways, and other endpoints.

### Source excerpt

Automation renews a certificate. Observability proves every endpoint is serving it and customers can complete a TLS handshake.

## Как мониторить Java-приложения: метрики, алерты и правило 80/20

DevFeed: [Как мониторить Java-приложения: метрики, алерты и правило 80/20](<https://devfeed.tech/articles/java-80-20-24881.md>)

Original publisher: [Read original article](<https://habr.com/ru/companies/yandex/articles/1068874/>)

Author: atushkanova (Яндекс)

Published: 2026-08-12T07:01:43Z

Content type: tutorial

Language: ru

Sources: [Яндекс - Как мы делаем Яндекс / Статьи](<https://devfeed.tech/sources/source.md>)

Topics: [Java](<https://devfeed.tech/topics/java.md>), [яндекс](<https://devfeed.tech/topics/tag-4004cf5948d3.md>)

Tags: [devops](<https://devfeed.tech/tags/devops.md>), [java](<https://devfeed.tech/tags/java.md>), [site-reliability-engineering](<https://devfeed.tech/tags/site-reliability-engineering.md>), [sre](<https://devfeed.tech/tags/sre.md>), [tag-4004cf5948d3](<https://devfeed.tech/tags/tag-4004cf5948d3.md>), [tag-617c72e79812](<https://devfeed.tech/tags/tag-617c72e79812.md>), [tag-622612a5798e](<https://devfeed.tech/tags/tag-622612a5798e.md>), [tag-65aad6d83235](<https://devfeed.tech/tags/tag-65aad6d83235.md>), [tag-73eb9b712998](<https://devfeed.tech/tags/tag-73eb9b712998.md>), [tag-7568ee66754b](<https://devfeed.tech/tags/tag-7568ee66754b.md>), [tag-a6a98345cb30](<https://devfeed.tech/tags/tag-a6a98345cb30.md>), [tag-b92bf5906bbd](<https://devfeed.tech/tags/tag-b92bf5906bbd.md>)

### AI overview

This article explains how to monitor Java applications using a focused set of technical metrics, useful alerts, business metrics, SLOs, and anomaly analysis. It presents an 80/20 approach and warns that excessive metrics and flapping alerts create information noise.

### Source excerpt

Хороший мониторинг помогает быстро понять, что происходит с приложением и куда смотреть в первую очередь. Для этого не нужно пытаться измерить всё: базовый набор технических метрик покрывает большинство типовых проблем, а бизнес-метрики, SLO и анализ аномалий помогают заранее замечать нетипичные отклонения. В Календаре мы называем этот подход правилом 80/20. Всем привет! Меня зовут Настя, я бэкенд-разработчик в Яндекс 360 и отвечаю за надёжность Календаря. В этой статье я покажу, какие метрики стоит взять за основу, как выбирать полезные алерты и чем дополнять базовый набор для оставшихся 20%. Читать далее

## AI SRE: Cut MTTR in Half with Autonomous Incident Resolution

DevFeed: [AI SRE: Cut MTTR in Half with Autonomous Incident Resolution](<https://devfeed.tech/articles/ai-sre-cut-mttr-in-half-with-autonomous-incident-resolution-12166.md>)

Original publisher: [Read original article](<https://www.port.io/blog/autonomous-incident-resolution>)

Author: Matar Peles

Published: 2026-08-10T11:34:38Z

Content type: article

Language: en

Sources: [Developer Experience & Platform Engineering Blog | Port](<https://devfeed.tech/sources/developer-experience-platform-engineering-blog-port.md>)

Topics: [site-reliability-engineering](<https://devfeed.tech/topics/site-reliability-engineering.md>), [incident](<https://devfeed.tech/topics/incident.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [monitor](<https://devfeed.tech/topics/monitor.md>), [dashboards](<https://devfeed.tech/topics/dashboards.md>), [Traces](<https://devfeed.tech/topics/traces.md>), [archive search](<https://devfeed.tech/topics/archive-search.md>), [Pull Request](<https://devfeed.tech/topics/pull-request.md>), [codex](<https://devfeed.tech/topics/codex.md>), [cursor](<https://devfeed.tech/topics/cursor.md>)

Tags: [agent](<https://devfeed.tech/tags/agent.md>), [ai](<https://devfeed.tech/tags/ai.md>), [codex](<https://devfeed.tech/tags/codex.md>), [cursor](<https://devfeed.tech/tags/cursor.md>), [dashboards](<https://devfeed.tech/tags/dashboards.md>), [datadog](<https://devfeed.tech/tags/datadog.md>), [incident](<https://devfeed.tech/tags/incident.md>), [monitor](<https://devfeed.tech/tags/monitor.md>), [monitoring](<https://devfeed.tech/tags/monitoring.md>), [on-call](<https://devfeed.tech/tags/on-call.md>), [sre](<https://devfeed.tech/tags/sre.md>), [traces](<https://devfeed.tech/tags/traces.md>), [workflow](<https://devfeed.tech/tags/workflow.md>)

### AI overview

This developer article describes an autonomous incident-resolution workflow built in Port. It argues that incident response time is largely spent reconstructing context from alerts, logs, dashboards, traces, ownership data, recent changes, and runbooks. The proposed agent-based workflow aims to use that full context to triage, diagnose, and fix production incidents, with a reported 50% reduction in MTTR. The supplied text ends during a discussion of why simply routing alerts to coding agents can fail.

### Source excerpt

See how an SRE agent workflow cuts MTTR in half, using full context to triage, diagnose, and fix incidents autonomously, all the way to a RCA.

## Automate Incident Intake with AI SRE Runbooks

DevFeed: [Automate Incident Intake with AI SRE Runbooks](<https://devfeed.tech/articles/automate-incident-intake-with-ai-sre-runbooks-13367.md>)

Original publisher: [Read original article](<https://www.harness.io/blog/automate-incident-intake-and-start-response-in-seconds>)

Author: Ryan Taylor

Published: 2026-08-10T00:00:00Z

Content type: tutorial

Language: en

Sources: [Harness Blog](<https://devfeed.tech/sources/harness-blog.md>)

Topics: [SRE](<https://devfeed.tech/topics/sre.md>), [incident](<https://devfeed.tech/topics/incident.md>), [Automation](<https://devfeed.tech/topics/automation.md>), [Slack](<https://devfeed.tech/topics/slack.md>), [zoom](<https://devfeed.tech/topics/zoom.md>), [Grafana](<https://devfeed.tech/topics/grafana.md>), [datadog](<https://devfeed.tech/topics/datadog.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [automation](<https://devfeed.tech/tags/automation.md>), [build](<https://devfeed.tech/tags/build.md>), [datadog](<https://devfeed.tech/tags/datadog.md>), [grafana](<https://devfeed.tech/tags/grafana.md>), [harness](<https://devfeed.tech/tags/harness.md>), [incident](<https://devfeed.tech/tags/incident.md>), [integrations](<https://devfeed.tech/tags/integrations.md>), [jira](<https://devfeed.tech/tags/jira.md>), [open](<https://devfeed.tech/tags/open.md>), [services](<https://devfeed.tech/tags/services.md>), [slack](<https://devfeed.tech/tags/slack.md>), [sre](<https://devfeed.tech/tags/sre.md>), [workflow](<https://devfeed.tech/tags/workflow.md>), [zoom](<https://devfeed.tech/tags/zoom.md>)

### AI overview

This article explains how Harness AI SRE runbooks automate incident intake and early response. Triggered by alerts, manual actions, or incident changes, a runbook can create tickets, open Slack channels, start Zoom bridges, set incident fields, and record actions in the incident timeline.

### Source excerpt

Automate incident intake with Harness AI SRE runbooks: auto-create tickets, open Slack channels, start Zoom bridges, and cut response time to seconds. | Blog

## Blue Green and Canary Deployments Explained

DevFeed: [Blue Green and Canary Deployments Explained](<https://devfeed.tech/articles/blue-green-and-canary-deployments-explained-17480.md>)

Original publisher: [Read original article](<https://kodekloud.com/blog/blue-green-and-canary-deployments-explained/>)

Author: Pramodh Kumar M

Published: 2026-08-09T16:30:08Z

Content type: tutorial

Language: en

Sources: [Kubernetes - KodeKloud Blog | DevOps, Cloud, Kubernetes, AI Tutorials & More](<https://devfeed.tech/sources/kubernetes-kodekloud-blog-devops-cloud-kubernetes-ai-tutorials-more.md>)

Topics: [Deployment](<https://devfeed.tech/topics/deployment.md>), [Software](<https://devfeed.tech/topics/software.md>), [Database](<https://devfeed.tech/topics/database.md>)

Tags: [argo-rollouts](<https://devfeed.tech/tags/argo-rollouts.md>), [automation](<https://devfeed.tech/tags/automation.md>), [blue-green-and-canary-deployments](<https://devfeed.tech/tags/blue-green-and-canary-deployments.md>), [ci-cd](<https://devfeed.tech/tags/ci-cd.md>), [ci-cd-pipeline](<https://devfeed.tech/tags/ci-cd-pipeline.md>), [cloud](<https://devfeed.tech/tags/cloud.md>), [database](<https://devfeed.tech/tags/database.md>), [deployment](<https://devfeed.tech/tags/deployment.md>), [deployment-strategies](<https://devfeed.tech/tags/deployment-strategies.md>), [devops](<https://devfeed.tech/tags/devops.md>), [dora-change-failure-rate](<https://devfeed.tech/tags/dora-change-failure-rate.md>), [expand-and-contract-migration](<https://devfeed.tech/tags/expand-and-contract-migration.md>), [feature-flags](<https://devfeed.tech/tags/feature-flags.md>), [guide](<https://devfeed.tech/tags/guide.md>), [kubernetes](<https://devfeed.tech/tags/kubernetes.md>), [progressive-delivery](<https://devfeed.tech/tags/progressive-delivery.md>), [release-management](<https://devfeed.tech/tags/release-management.md>), [rollback](<https://devfeed.tech/tags/rollback.md>), [rolling-update](<https://devfeed.tech/tags/rolling-update.md>), [schema](<https://devfeed.tech/tags/schema.md>), [sre](<https://devfeed.tech/tags/sre.md>), [traffic-splitting](<https://devfeed.tech/tags/traffic-splitting.md>), [zero-downtime-deployment](<https://devfeed.tech/tags/zero-downtime-deployment.md>)

### AI overview

This guide explains blue-green and canary deployment strategies for replacing running software versions. It emphasizes that effective rollback depends on detecting problems with reliable metrics and that database schema changes can limit reversibility.

### Source excerpt

Both strategies buy you the same thing, which is a cheap way to be wrong. The mechanism is the easy part, and the two hard parts are noticing you are wrong and dealing with the database.

## Eric Schwartz on what it takes to run an AI SRE at petabyte scale

DevFeed: [Eric Schwartz on what it takes to run an AI SRE at petabyte scale](<https://devfeed.tech/articles/eric-schwartz-on-what-it-takes-to-run-an-ai-sre-at-petabyte-scale-16015.md>)

Original publisher: [Read original article](<https://workos.com/blog/eric-schwartz-traversal-ai-sre-petabyte-scale>)

Author: WorkOS

Published: 2026-08-07T00:00:00Z

Content type: article

Language: en

Sources: [WorkOS Blog](<https://devfeed.tech/sources/workos-blog.md>)

Topics: [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [site-reliability-engineering](<https://devfeed.tech/topics/site-reliability-engineering.md>), [data-platforms](<https://devfeed.tech/topics/data-platforms.md>), [telemetry](<https://devfeed.tech/topics/telemetry.md>), [observability ai agents](<https://devfeed.tech/topics/observability-ai-agents.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [data](<https://devfeed.tech/tags/data.md>), [data-platforms](<https://devfeed.tech/tags/data-platforms.md>), [on-call](<https://devfeed.tech/tags/on-call.md>), [production](<https://devfeed.tech/tags/production.md>), [root-cause-analysis](<https://devfeed.tech/tags/root-cause-analysis.md>), [sre](<https://devfeed.tech/tags/sre.md>), [telemetry](<https://devfeed.tech/tags/telemetry.md>)

### AI overview

An interview with Traversal product manager Eric Schwartz examines how the company operates an AI site reliability engineer for large enterprises. The article explains that petabyte-scale telemetry requires continuously analyzing, compressing, and indexing data ahead of runtime, with an SRE-focused tool and prompt harness. Traversal reports that deployments are generally running in production within a week with minimal tuning, supported by forward-deployed engineering for last-mile optimization.

### Source excerpt

Traversal PM Eric Schwartz on data platforms, routing models by severity, and the permission ladder toward self-driving production, from AI Engineer 2026.

## What your AI SRE can't see (and what you can do about it)

DevFeed: [What your AI SRE can't see (and what you can do about it)](<https://devfeed.tech/articles/what-your-ai-sre-can-t-see-and-what-you-can-do-about-it-11736.md>)

Original publisher: [Read original article](<https://www.gremlin.com/blog/what-your-ai-sre-cant-see-and-what-you-can-do-about-it>)

Author: Ryan Detwiller

Published: 2026-08-06T00:00:00Z

Content type: opinion

Language: en

Sources: [Gremlin Blog](<https://devfeed.tech/sources/gremlin-blog.md>)

Topics: [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [SRE](<https://devfeed.tech/topics/sre.md>), [incident](<https://devfeed.tech/topics/incident.md>), [Availability](<https://devfeed.tech/topics/availability.md>), [telemetry](<https://devfeed.tech/topics/telemetry.md>), [Latency](<https://devfeed.tech/topics/latency.md>), [Memory Leaks](<https://devfeed.tech/topics/memory-leaks.md>), [Deployment](<https://devfeed.tech/topics/deployment.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [availability](<https://devfeed.tech/tags/availability.md>), [config](<https://devfeed.tech/tags/config.md>), [dependency](<https://devfeed.tech/tags/dependency.md>), [deployment](<https://devfeed.tech/tags/deployment.md>), [latency](<https://devfeed.tech/tags/latency.md>), [load-balancer](<https://devfeed.tech/tags/load-balancer.md>), [memory](<https://devfeed.tech/tags/memory.md>), [outage](<https://devfeed.tech/tags/outage.md>), [outages](<https://devfeed.tech/tags/outages.md>), [sre](<https://devfeed.tech/tags/sre.md>)

### AI overview

The article argues that AI SRE tools can speed up triage, reduce alert fatigue, and automate frontline incident response, but they do not solve all reliability problems. It identifies gaps including acting only after failures begin and being unable to predict sudden failures without detectable warning signals.

### Source excerpt

AI SRE is having a moment. And let's be honest: faster triage, less alert fatigue, and automated frontline response are wins for understaffed teams. But there are still five gaps in their capabilities, and if you don't understand those gaps before you deploy, you'll find out during an outage.

## Cloud provider postmortems: volume vs depth

DevFeed: [Cloud provider postmortems: volume vs depth](<https://devfeed.tech/articles/cloud-provider-postmortems-volume-vs-depth-34008.md>)

Original publisher: [Read original article](<https://sridharrajarao.com/blog/cloud-postmortems-volume-vs-depth/>)

Author: Sridhar Rajarao

Published: 2026-08-05T00:00:00Z

Content type: opinion

Language: en

Sources: [Sridhar Rajarao](<https://devfeed.tech/sources/sridhar-rajarao.md>)

Topics: [Cloud](<https://devfeed.tech/topics/cloud.md>), [incident](<https://devfeed.tech/topics/incident.md>), [SRE](<https://devfeed.tech/topics/sre.md>), [site-reliability-engineering](<https://devfeed.tech/topics/site-reliability-engineering.md>), [engineering-culture](<https://devfeed.tech/topics/engineering-culture.md>)

Tags: [2017](<https://devfeed.tech/tags/2017.md>), [2025](<https://devfeed.tech/tags/2025.md>), [2026](<https://devfeed.tech/tags/2026.md>), [aws](<https://devfeed.tech/tags/aws.md>), [azure](<https://devfeed.tech/tags/azure.md>), [cloud](<https://devfeed.tech/tags/cloud.md>), [dynamodb](<https://devfeed.tech/tags/dynamodb.md>), [engineering-culture](<https://devfeed.tech/tags/engineering-culture.md>), [gcp](<https://devfeed.tech/tags/gcp.md>), [incident](<https://devfeed.tech/tags/incident.md>), [incident-management](<https://devfeed.tech/tags/incident-management.md>), [postmortems](<https://devfeed.tech/tags/postmortems.md>), [s3](<https://devfeed.tech/tags/s3.md>), [sre](<https://devfeed.tech/tags/sre.md>), [transparency](<https://devfeed.tech/tags/transparency.md>), [writeup](<https://devfeed.tech/tags/writeup.md>)

### AI overview

The article compares public postmortem practices among Google Cloud, Azure, and AWS. It argues that Google Cloud emphasizes high volume and speed, Azure emphasizes detailed transparency and customer accountability, and AWS publishes fewer writeups with greater depth and industry influence.

### Source excerpt

GCP publishes 100+ postmortems a year. AWS publishes almost none. Azure has become the transparency leader. What each posture reveals about engineering culture, and what SREs should steal from all three.

[Next page](<https://devfeed.tech/tags/sre.md?cursor=WyIyMDI2LTA4LTA1VDAwOjAwOjAwKzAwOjAwIiwgImNkMDYwZWNmLWJjZTctNGU2MS05YmU3LTIxMTUzM2U4N2JhNyJd>)